ANALYZING THE IMPACT OF BIG DATA AND BUSINESS ANALYTICS IN ENHANCING DEMANDDRIVEN FORECASTING IN RETAILING

Dr. Jaipal Rathod and Mr. Raj Kumar
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Dr. Jaipal Rathod: Central University of Karnataka
Mr. Raj Kumar: Senior Manager, Punjab National Bank

International Journal of Entrepreneurship, 2021, vol. 25, issue 2

Abstract: Purpose: The purpose of this paper is to analyzing the impact of big data and business analytics in enhancing demand-driven forecasting in retailing sector in the Indian context. The study highlight the challenges and opportunities involving big data and analytics for enhancing the process of retailing. The retailing process involves different procedures such as gathering information, analyzing data, providing solutions so that critical business decisions are taken adequately. It includes the intensification of a large volume of data by using advanced technologies such as big data and business analytics so that retailing business is enhanced. Design/methodology/approach: The study adopted secondary source of data from different over views of bigdata impacting on tetailing sector and study also examined that the application of big data and business analytics enhances the involvement of the customers and their interaction with the retailers during the retailing process. It helps in bridging the gap and establishing a good connection with customers. Originality/value: The main aim of the research is to analyze the impact of big data and business analytics in enhancing demand-driven forecasting in retailing. The study also highlights the challenges and opportunities involving big data and analytics for enhancing the process of retailing. The research identified that big data and business analytics help in predicting future performance, price optimizing, and forecasting demand. Managerial and Social Implications: the study helps retailers It was found that technologies also help in predicting trends and identifying target customers. Thus, it can be concluded that big data and business analytics are essential technologies that are highly used by the firm in the retail sector to capture customer experience, forecast sales, and provide normative decision suggestions.

Keywords: Big Data; Retailing; Analytics; Data Science; Automation; Forecasting (search for similar items in EconPapers)
JEL-codes: F23 (search for similar items in EconPapers)
Date: 2021
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Persistent link: https://EconPapers.repec.org/RePEc:ris:ijentr:0179

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